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https://issues.apache.org/jira/browse/SPARK-12467?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15994849#comment-15994849
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John Berryman commented on SPARK-12467:
---------------------------------------
Here's a slightly different example that I think should point out another
problem
{code}
from datetime import datetime
from pyspark.sql import Row
rows = [
Row(number=1, letters='real1', some_date=datetime(2017,12,1,3,15)),
Row(number=2, letters='real2', some_date=datetime(2017,12,2,3,15)),
Row(number=3, letters='real3', some_date=datetime(2017,12,3,3,15)),
]
rows_rdd = spark.sparkContext.parallelize(rows)
df = spark.createDataFrame(rows_rdd)
spark.sql('CREATE DATABASE test_trash')
df.write.mode(saveMode='overwrite').saveAsTable('test_trash.thingy')
schema = spark.sql('SELECT number, letters, some_date FROM
test_trash.thingy').schema
df = spark.createDataFrame(rows_rdd, schema)
df.count()
{code}
- In the first part of the code I define a bunch of Rows with the schema
implicit schema {{'number':=int, 'letters'=string, 'some_date'=date}}.
- In the second part of code I query a table made from that data set and I
query the fields in the same order: {{number, letters, some_date}} so the
schema should be exactly the same. (Though I still think order shouldn't matter
since Rows have named fields.)
- In the third part of the code I attempt to create a dataframe using the
original data and the schema that was created _from_ the original data. But I
get an error saying that that the original data doesn't fit _in it's own
implied schema_.
If you can't write data into it's own implied schema, then this is a bug.
> Get rid of sorting in Row's constructor in pyspark
> --------------------------------------------------
>
> Key: SPARK-12467
> URL: https://issues.apache.org/jira/browse/SPARK-12467
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.5.2
> Reporter: Irakli Machabeli
> Priority: Minor
>
> Current implementation of Row's __new__ sorts columns by name
> First of all there is no obvious reason to sort, second, if one converts
> dataframe to rdd and than back to dataframe, order of column changes. While
> this is not a bug, nevetheless it makes looking at the data really
> inconvenient.
> def __new__(self, *args, **kwargs):
> if args and kwargs:
> raise ValueError("Can not use both args "
> "and kwargs to create Row")
> if args:
> # create row class or objects
> return tuple.__new__(self, args)
> elif kwargs:
> # create row objects
> names = sorted(kwargs.keys()) # just get rid of sorting here!!!
> row = tuple.__new__(self, [kwargs[n] for n in names])
> row.__fields__ = names
> return row
> else:
> raise ValueError("No args or kwargs")
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